In response to a growing demand for high-quality and internationally-comparable statistics, FAO develops, implements and promotes methods and standards to guide national data producers in generating and using sound statistics. In particular, the Organization is committed to provide national statistical systems with internationally recognized definitions, concepts and classifications as well as methodological guidance for the production of high quality statistics related to food and agriculture.
This interface allows you to search for statistical classifications, guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources. You can search by SUBJECT (general, agriculture, forestry, fishery and aquaculture, and natural resources) or use the ADVANCED SEARCH to search by keyword, country, language and lead authoring unit/office. Comments, suggestions and inquiries can be addressed to: [email protected].
You can access here all the statistical guidelines and handbooks, technical reports, working papers and methodological documents, and capacity development resources.
Type a keyword in the free text search box or refine your search by keyword, country, language and lead authoring unit/office.
Comments, suggestions and inquiries can be addressed to: [email protected].
Abstract: Prepared in the framework of the Global Strategy to improve Agricultural and Rural Statistics (GSARS), this technical paper on identifying the most appropriate sampling frame for specific landscape types is the result of a comprehensive literature review on the subject, followed by a gap analysis and development of innovative methodological proposals for addressing any issues that emerged.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Prepared by the Global Strategy to Improve Agricultural and Rural Statistics (GSARS), this technical report on Developing More Efficient and Accurate Methods for the Use of Remote Sensing is the result of a comprehensive literature review on the subject, followed by a gap analysis and, finally, the development of innovative methodological proposals for addressing the various issues arising.
Abstract: This paper, which is part of FAO Statistics Working Paper Series, presents the methodological framework used by FAO’s Statistics Division to now-cast consumer food inflation at regional level. Hybrid ARIMA-GARCH models are estimated for each region, with additional explanatory variables constructed from a large and high-frequency dataset.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This paper, which is part of FAO Statistics Working Paper Series, proposes a methodology to select indicators in multidimensional assessments, such as the ones required for the measurement of food security. By linking the overarching objectives of the evaluation to the nature of the indicators, this methodology is able to discriminate among the hundreds of indicators proposed.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This paper, which is part of FAO Statistics Working Paper Series, reports on refinements to the methodology for estimating the prevalence of undernourishment that were adopted during the preparation of the State of Food Insecurity in the World report 2014.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This paper, which is part of FAO Statistics Working Paper Series, elaborates on some of the methodological aspects linked to assessing food insecurity, with special reference to the practice that FAO has been following in monitoring the state of food insecurity in the world.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Following a review of developments in undernourishment in a population, this paper - which is part of FAO Statistics Working Paper Series - shows that the formulation of PU within the bivariate distribution framework is inappropriate. Subsequently, the relevance of the univariate approach is clarified.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: This report, which is part of FAO Statistics Working Paper Series, discusses new knowledge on anthropogenic greenhouse gas (GHG) emissions from agriculture, forestry and other land use (AFOLU) activities made available through the new FAOSTAT Emission database.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: Understanding to what extent and speed agricultural commodity price changes on international markets are transmitted to consumers is key in assessing the vulnerability of households to price shocks. This paper, which is part of FAO Statistics Working Paper Series, provides estimates of the transmission of price changes from international commodity markets to consumers in different regions.
Lead authoring unit/office: Statistics Division (ESS)
Abstract: These guidelines are the result of the first comprehensive effort to develop a standard methodology to assess countries’ capacity to produce agricultural statistics. The presented methodology takes into account previous similar international efforts, particularly those led by the International Monetary Fund (IMF), the World Bank (WB), Paris 21, and more recently, the United Nations Statistical Commission (UNSC), for building a standard framework to assess statistical systems’ capacity and data quality. The assessment framework covers the institutional infrastructure, human and financial resources available, statistical methods and practices, and data availability at the country level. The guidelines also present a set of operational tools and methods for carrying out assessments in conformity with the proposed framework, which has been developed through an extensive consultative process and pilot testing in all regions. In addition to a standard questionnaire and guidelines on data collection, a set of indicators on different dimensions and capacity elements are also provided. These indicators will serve as a tool for monitoring progress at country level and for providing counterfactual information necessary for measuring impact in countries.
Lead authoring unit/office: Statistics Division (ESS)
